ReviewCurrent nutrition reports2025
Artificial Intelligence in Clinical Nutrition: Bridging Data Analytics and Nutritional Care.
Review in Current nutrition reports, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers, 2 of them syntheses that pooled it.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
10 citing papers in PubMed, 2 syntheses or guidelines pooled it.
- Nutritional prehabilitation in patients with head and neck cancer: an evidence mapping analysis.Supportive care in cancer : official journal of the Multinational Association of Supportive Care in Cancer · 2026Pooled it
- Systematic Review of Artificial Intelligence Applications in Clinical Trials for Central Nervous System Injuries.Current neuropharmacology · 2026Pooled it
- Artificial Intelligence in Clinical Nutrition: Current Uses, Challenges, and Opportunities.Nutrients · 2026Review
- Review
- Early Risk Stratification for 30-Day Mortality After In-Hospital Cardiac Arrest: SHAP Interpretable CatBoost Model with m-NUTRIC and Micronutrient Biomarkers.Journal of clinical medicine · 2026Article
- Article
- Artificial Intelligence in Parenteral Nutrition: Enhancing Patient Outcomes Through Global Experience and the Bulgarian Context.Nutrients · 2026Review
- Artificial Intelligence in the Nutritional Management of Inflammatory Bowel Disease: A Scoping Review.Journal of multidisciplinary healthcare · 2026Review
- Feeding intelligence: comparative evaluation of ChatGPT and clinical guidelines for nutritional management in head and neck cancer.Journal of translational medicine · 2025Article
- Benchmarking ChatGPT and Other Large Language Models for Personalized Stage-Specific Dietary Recommendations in Chronic Kidney Disease.Journal of clinical medicine · 2025Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
6 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
purpose of reviewThis review explores how artificial intelligence can help advance clinical nutrition and address nutrition education and practice challenges. It highlights the role of AI, mainly through advanced clinical decision-making using generative AI, in supporting clinicians as they develop personalized nutrition interventions for individual patients. Furthermore, the review discusses how AI technologies are helping to close the knowledge gap in nutrition and delivering real-time, evidence-based insights to healthcare professionals. RECENT
findingsAI processes, such as machine learning and natural language processing, have shown promising results in predicting nutritional outcomes and complications, such as malnutrition and central line-associated bloodstream infections. Studies highlight the capability of AI to efficiently process large datasets, identify key risk factors, and provide real-time support to clinicians. Furthermore, AI can personalize educational content, making complex nutritional concepts more accessible. AI has demonstrated multiple potential use cases in nutrition. However, much work still needs to be done to evaluate its accuracy, accessibility and ethical considerations.
Indexed as
Identifiers
40608213What Socratic holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the Socratic graph.